Centro de Documentacion de Fundación MAPFRE - Gaussian proces models for mortality rates and improvement factors

MAP20180032059

Gaussian proces models for mortality rates and improvement factors / Mike Ludkovski, Jimmy Risk, Howard Zail

Sumario: We develop a Gaussian process (GP) framework for modeling mortality rates and mortality improvement factors. GP regression is a nonparametric, data driven approach for determining the spatial dependence in mortality rates and jointly smoothing raw rates across dimensions, such as calendar year and age. The GP model quantifies uncertainty associated with smoothed historical experience and generates full stochastic trajectories for out-of-sample forecasts

En: Astin bulletin. - Belgium : ASTIN and AFIR Sections of the International Actuarial Association = ISSN 0515-0361. - 03/09/2018 Volumen 48 Número 3 - septiembre 2018 , p. 1307-1347

1. Cálculo actuarial . 2. Modelos actuariales . 3. Modelos predictivos . 4. Mortalidad . 5. Data driven . I. Risk, Jimmy . II. Zail, Howard . III. Title.